The Enterprise Data Management Operations group is responsible for effective and consistent Data Management of the bank’s data which is deemed critical: Used in external reporting, used to continuously provide information to the bank’s board, and data whose deficiency can cause financial loss/severe Impact to the customer.

    The centralized Enterprise Data Management Operations group performs activities required to provide effective control of the data which is deemed critical to the bank.

    Our Delivery

    Phyton delivered the following Data Management Operations and Data Governance work streams:

    Data Lineage – Work closely with the different business functions in order to capture the Critical Data Elements (CDEs) used in their end-user processes; Then work with the upstream data providers to capture the data lineage from downstream back to inception; Identify the CDEs’ Business and IT data owners throughout the data lineage chain.

    Data Quality Profiling – Lead data quality workshops to recommend and capture business rules for the identified CDEs.

    Data Quality Monitoring – Track and monitor the data quality issues that are discovered and provide status to senior management.

    Data Quality Issue Remediation – Once data quality issues are discovered, 1) Work with downstream business end-users in order to provide Tactical data quality remediation; 2) Work with upstream source systems’ Operations and IT in order to provide Strategic data quality remediation work effort analysis, monitor progress and report status to senior management.

    Data Governance – Creation of Policies & Procedures and the adoption and training across the CDO function and the business

    Business Glossary Creation and Tooling, Meta Data Management strategy, Data dictionary

    Risk & Control Assessments

    DM and DG Tools – Selection and implementation

    Our Value

    Phyton Consulting’s plan and delivery created a clear
    road map and plan for this case.

    1
    Phyton was able to manage and deliver
    the Data Lineage documentation, DQ rules,
    Issue Remediation plans, and a clear
    roadmap on how to roll out the policies
    and procedures for adoption.
    2
    Phyton enabled the successful
    implementation of the selected
    DM and DG tools.
    3
    Phyton helped produce a clear road
    map and plan for the next stage of
    the project and the creation of a golden
    source data repository for Risk & Finance.

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